Posts Tagged ‘DevoxxUK2026’
[DevoxxUK2026] Aspiring Speakers: Learning Python to Buy Shoes
Lecturer
Isaac Oldwood is an emerging software engineer and public speaker passionate about accessible, project-based learning. His journey from mathematics student to developer exemplifies practical skill acquisition through real-world problem-solving.
Abstract
Isaac Oldwood shares a personal narrative of mastering Python by tackling an everyday challenge: automating the purchase of limited-edition sneakers. This beginner-friendly account traces the evolution from rudimentary automation scripts to sophisticated API interactions, highlighting key lessons on learning through failure, iteration, and building relevant projects.
From MATLAB to Real-World Automation: A Developer’s Origin Story
Beginning in 2016 as a first-year mathematics student at the University of Nottingham, Isaac encountered programming through a compulsory MATLAB module. Recognizing the value of coding skills for modern mathematicians, he excelled yet questioned his academic path upon receiving strong results. Seeking guidance through traditional searches, he discovered that foundational knowledge in variables and control structures should pair with building practical projects aligned with personal interests.
The chosen project involved acquiring Yeezy Boost 350 V2 “Bred” sneakers. Initial attempts employed PyAutoGUI for keyboard and mouse automation, relying on screen coordinates and arbitrary sleep timers. These approaches proved brittle against dynamic web interfaces and competitive release timings.
Subsequent iterations leveraged Selenium for browser automation, enabling direct interaction with HTML elements and conditional waits. This advancement improved reliability as scripts adapted to page changes. Further research into inter-computer communication revealed APIs, leading to direct HTTP interactions using the Requests library. By reverse-engineering checkout flows, Isaac implemented PUT requests to cart endpoints and POST requests for payment processing, dramatically reducing latency compared to full page loads burdened by images, trackers, and fonts.
Scalability challenges emerged when extending the solution to housemates. Synchronous execution created unfair queuing. Transitioning to asynchronous operations with HTTPX allowed concurrent checkouts, ensuring equitable opportunity at release moments.
Despite technical refinements, the script ultimately failed against robust anti-bot measures deployed by the retailer. Success arrived through manual effort: queuing physically outside a store at dawn. This outcome reinforced that automation serves as a learning vehicle rather than a guaranteed solution.
Conclusion
Isaac’s engaging story underscores fundamental truths about technical education. Learning proves enjoyable when rooted in passion projects. Failure constitutes an integral component of growth, yielding deeper insights than initial successes. Building tangible solutions to personal problems accelerates skill development far beyond theoretical study. Aspiring developers benefit immensely from identifying relevant challenges and iterating relentlessly toward mastery.
Links:
[DevoxxUK2026] Aspiring Speakers: From Replacement to Rocket Fuel – Launching Your Tech Career
Lecturer
Sudi Mandyam is an Engineering Manager at Intradiem, bringing extensive experience in software engineering, site reliability engineering, and cloud technologies. With a background from Visvesvaraya Technological University and roles at organizations including Fastute.io and Navro, Sudi has established himself as a problem solver, leader, writer, and mentor in the technology sector. His insights into AI-driven transformations stem from hands-on leadership in engineering teams navigating rapid industry shifts.
Abstract
In this insightful presentation, Sudi Mandyam challenges prevailing narratives around artificial intelligence displacing developers. Instead, he positions AI as a powerful accelerator for career advancement, particularly for aspiring technologists. Through historical context, evolving AI capabilities, and practical demonstrations, the talk equips attendees with strategies to transition from fearing obsolescence to embracing architectural leadership in an agentic AI era.
The AI Shift: Perception Versus Reality
Sudi opens by highlighting the interconnected nature of technology, opportunities, and problems. He notes that while some perceive AI as a threat to coding professions, this view represents only one facet of a multifaceted evolution. Drawing an analogy to brick-making, he emphasizes that even as AI generates code, human architects remain essential for designing and constructing robust systems.
The presentation traces the rapid progression of AI frameworks over recent years. In 2022, tools like ChatGPT emerged as disruptors, initially seen as potential replacements for search engines. By 2024, solutions such as GitHub Copilot and advanced prompting techniques focused on enhancing speed and efficiency in code generation. However, challenges persisted, including model hallucinations arising from suboptimal prompts or model selections.
Advancing into 2025, agentic programming gained prominence with tools like Cursor and Windsurf, offering improved context handling for microservices and classes, thereby reducing “slop code.” Despite these advances, widespread adoption without adequate guardrails led to security concerns and operational issues. Sudi identifies the current landscape as the “agentic engineering era,” a new discipline layered atop traditional software engineering. Here, context-aware agents function as collaborative colleagues rather than mere coding engines, empowered by frameworks such as CrewAI and Google ADK.
A persistent limitation remains: agents perform only as effectively as the context provided. “Garbage in, garbage out” continues to apply, underscoring the need for sophisticated knowledge management.
Building Organizational Intelligence: LLM Wiki and Intelligent Triage
To address contextual gaps, Sudi introduces the LLM Wiki pattern, inspired by concepts from Andre Karpathy. This approach curates organizational information into a consumable markdown format via an incremental wiki compiler, creating a “second brain” that persists beyond individual experts. Unlike traditional retrieval-augmented generation that may require repeated parsing, the wiki maintains coherent, evolving knowledge repositories.
This second brain proves invaluable across scenarios, particularly incident management. Sudi presents the Intelligent Triage Mesh, which integrates LLM Wiki data, metrics, runbooks, and observability traces from tools like OpenTelemetry and DataDog. A multi-agent orchestration engine evaluates incidents, using confidence thresholds to determine whether automated remediation suffices or human intervention is required.
A live demonstration illustrates these principles in action. Simulating payment failures, an orchestrator leveraging the LLM Wiki decides between auto-remediation and human escalation. Implemented in Go with Google ADK, the system features a main Gemini-powered orchestrator alongside local models for specialized agents. Global policy overrides, managed via the second brain, allow non-technical stakeholders like product managers to update behaviors without code changes.
This methodology significantly improves key metrics such as Mean Time to Recovery (MTTR) within DORA frameworks, transforming incident resolution from hours to minutes.
Conclusion
Sudi Mandyam masterfully reframes AI not as a replacement engine but as rocket fuel for technical careers. By advocating a shift to agentic engineering mindsets and demonstrating practical implementations like contextual wikis and intelligent orchestration, the talk provides actionable pathways for developers to thrive amid technological disruption. Ultimately, the message resonates clearly: problems breed opportunities, and proactive engagement with AI tools positions aspiring speakers and engineers for sustained success.